Community Comment: Part 19 - Firms have more choices than just buy vs build
- Firms have more choices than vendors admit
- The "buy vs build" choice is nuanced
- Commercial & open source fall on spectrum
- Blanket $ statements cannot be made
The comments I provided in reaction to a community discussion thread.
CEO at ELT platform firm:
Do you think your data team is special?
It’s not.
You take one of two approaches.
Strategy 1. Invest in people in service of open source software.
Strategy 2. Invest in SaaS software in service of people.
Your approach directly determines who you hire, how you spend money, and which technologies you use.
Let me outline the two approaches in more detail.
Approach 1.
Teams that invest in people in service of open source software.
This is common in a handful of situations:
– When data teams are born out of engineering teams.
– Data teams within particular industry verticals – like healthcare and financial services.
– Very large enterprises (i.e. the Fortune 500).
– Non-US companies (where SaaS software for data management is less accessible).
These teams invest heavily in headcount.
The biggest line item for the data team will be engineering talent on staff.
Approach 2.
Teams that invest in SaaS software in service of people.
This is common in a handful of scenarios:
– When data teams are built out under a business function.
– Data teams within high-growth industries, with lighter weight procurement processes (eCommerce, marketing, etc.).
– Mid-market companies with lean teams.
– US-based companies.
These teams invest heavily in SaaS software.
As a result, budgets are more evenly split between headcount (typically very lean teams) and SaaS software.
How can you tell which type of team you’re building?
There are two easy tests:
1. When you see a problem and need a solution, do you first try to build in-house? Or do you first try to find a SaaS solution?
2. Is your team primarily budgeting for headcount or software?
I only came to this realization after I started selling to data teams.
Why?
As a vendor in the data world, you start by thinking all data teams are the same.
At [ELT platform firm], we’re a SaaS solution.
We’ve realized we’re not a good fit for teams that invest in people in service of open source software.
The idea of leveraging a SaaS solution goes against the culture, the procurement methodology, and the architecture of those companies.
Have other vendors arrived at the same realization?
For those people in analytics.
Which type of data team are you building?
Gfesser: Interesting thoughts. In the context of your argument, I would typically call strategy #1 "invest in people in service of custom development" because the opposite of buying software is building software, and making use of open source tech is one of the options for construction. Tech savvy firms will obviously make heavy use of open source tech. But there is something else to consider that I often see missing in discussions such as this: buying commercialized open source. In other words, commercial software which has been built on open source. AWS and GCP, for example, provide quite a few examples of such offerings. But I don't think the quantities of talent for these two strategies are at opposite ends of a spectrum.